Corticomotor excitability of the pelvic floor muscles in females: Characteristics of motor evoked potentials and test–retest reliability
Bibliographic record
Abstract
OBJECTIVES: To (1) design an efficient TMS protocol to elicit motor evoked potentials (MEPs) from female pelvic floor muscles (PFMs), (2) describe the characteristics of PFM MEPs and silent periods (SPs), (3) compare PFM MEP characteristics with nearby muscles and (4) determine the test-retest reliability of PFM MEP characteristics and SP duration. METHODS: Through a cross-sectional, observational design, adult females were tested at two sessions separated by one week. Single-pulse TMS was delivered over the motor cortex and motor responses were recorded from three PFMs, the lateral abdominal wall (LAW) and the hip adductors (ADD). MEP characteristics were compared among the PFMs and with those from the ADD and LAW. Test-retest reliability was examined using intra-class correlation coefficients (ICCs). RESULTS: Nearly all participants (n = 40/41) exhibited measurable SPs in the pubovisceralis and at least one other PFM. PFM MEPs exhibited shorter onset latencies than those of ADD and LAW. ICCs ranged from good to excellent, except for peak latency, which was poor. Yet all measures displayed high between-participant variance. CONCLUSION: Investigating reliable TMS-induced motor responses in the PFMs of females is achievable using our protocol. SIGNIFICANCE: Our findings highlight the possibility of extending TMS applications to investigate changes in corticomotor excitability that may contribute to conditions that are associated with high PFM tone, such as vulvovaginal pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".